人体姿势估计关键点提取 - Python 代码示例 - 常规

将姿势估计结果添加到列表中

pose_results.append([folder_name, results.pose_landmarks.landmark[mp_pose.PoseLandmark.NOSE].x,
                                 results.pose_landmarks.landmark[mp_pose.PoseLandmark.NOSE].y,
                                 results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_SHOULDER].x,
                                 results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_SHOULDER].y,
                                 results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_SHOULDER].x,
                                 results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_SHOULDER].y,
                                 results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_ELBOW].x,
                                 results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_ELBOW].y,
                                 results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_ELBOW].x,
                                 results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_ELBOW].y,
                                 results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_WRIST].x,
                                 results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_WRIST].y,
                                 results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_WRIST].x,
                                 results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_WRIST].y,
                                 results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_HIP].x,
                                 results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_HIP].y,
                                 results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_HIP].x,
                                 results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_HIP].y,
                                 results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_KNEE].x,
                                 results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_KNEE].y,
                                 results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_KNEE].x,
                                 results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_KNEE].y,
                                 results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_ANKLE].x,
                                 results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_ANKLE].y,
                                 results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_ANKLE].x,
                                 results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_ANKLE].y])

获取人体姿势信息

pose_data = []
for landmark in results.pose_landmarks.landmark:
    pose_data.append(landmark.x)
    pose_data.append(landmark.y)
    pose_data.append(landmark.z if landmark.z is not None else 0)

这段代码使用循环遍历所有关键点，并提取每个关键点的 x、y 坐标，以及可选的 z 坐标。如果 z 坐标不存在，则使用 0 填充。

总结

通过以上代码示例，您可以轻松地从人体姿势估计结果中提取关键点信息。这些信息可以用于各种应用，例如：

姿势分析
人机交互
运动训练
动画制作

希望本文能帮助您更好地理解人体姿势估计的关键点提取方法。